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This website was developed as the Final Project for Harvard OpenCourseWare CS50 Web course.

The website explores the basics of statistics - a branch of mathematics that pertains to the collection, analysis, interpretation or explanation, and presentation of data.[10] Each page is dedicated to a topic within statistics, describing common terminology, numerical measures (also collectively referred to as "statistics")[1,p.2] and graphical representations.

The concepts that are covered on the pages of this website are:

Data: as measurements or observations that are collected as a source of information.[3] This section covers definitions, types of data, as well as principles and methods of collecting data.

  • Types of Data - the two groups that most data falls into are quantitative (numerical) or qualitative (categorical) data.[1,p.50]
  • Population & Sample - a population is the complete group that is being studied or referred to, and a sample is a subset of units from a population, selected to represent all units in that population.[3]
  • Surveys - the most common type of observational study,[1,p.11,62] that is used to collect statistical data.
  • Experiments - a type of controlled study[3] that is used to collect statistical data.

Statistics: as descriptive statistics, one of the two major ways of summarising and representing "the big picture" by using numbers to describe the important features of data.[1,pp.14-15]

  • Mean - the sum of the value of each observation in a dataset divided by the number of observations, also known as the "arithmetic average".[3]
  • Median - the middle value in distribution when the values are arranged in ascending or descending order.[3]
  • Standard Deviation - the measure of the spread of the data around the mean.[3]
  • Percentiles - a statistic that reports relative standing and marks a certain percentage of the way through the data.[1,pp.88-89]

Charts: as the second of the two major ways of summarising and representing "the big picture" by using graphical representations to describe data.[1,p.14,108]

  • Pie Chart - one of the most common types of graphical representation of qualitative data that that breaks the data down by group.[1,p.96]
  • Bar Graph - a type of graph in which each column (plotted either vertically or horizontally) represents a categorical variable or a discrete ungrouped numeric variable[3]
  • Histogram - a type of chart that provides a snapshot of all data broken down into numerically ordered groups.[1,p.108]
  • Line Graph - graphical representation of collection of observations obtained through repeated measurements over time.[3]
  • Boxplot - a one-dimensional graph of numerical data divided in four parts, with each part containing 25% of the data.[1,p.120]

Data Sets: as collections of observations[3] organised in a grid.

  • Inbuilt Data Sets - this section lists and explains all data sets that are available to all users.
  • My Data Sets - this section allows users upload, edit and delete their own data structures to use elsewhere on the website.

Sources: as a list of all sources referenced in and used for this website.


This project was built using the following programming languages and tools:

  • Django framework
  • A handful of Python libraries, most notably Pandas and Plotly
  • HTML with Sass CSS, Bootstrap, MathJax and Dropzone
  • Javascript